scholarly journals Organoid technology for personalized pancreatic cancer therapy

2021 ◽  
Author(s):  
Axel Bengtsson ◽  
Roland Andersson ◽  
Jonas Rahm ◽  
Karthik Ganganna ◽  
Bodil Andersson ◽  
...  
Keyword(s):  
Drug Screening ◽  
Response Prediction ◽  
Metabolic Imaging ◽  
Ductal Adenocarcinoma ◽  
3D Bioprinting ◽  
Preclinical Models ◽  
Liquid Handling ◽  
Technical Solutions ◽  
Pancreatic Cancer Therapy ◽  
Related Mortality

Abstract Background Pancreatic ductal adenocarcinoma has the lowest survival rate among all major cancers and is the third leading cause of cancer-related mortality. The stagnant survival statistics and dismal response rates to current therapeutics highlight the need for more efficient preclinical models. Patient-derived organoids (PDOs) offer new possibilities as powerful preclinical models able to account for interpatient variability. Organoid development can be divided into four different key phases: establishment, propagation, drug screening and response prediction. Establishment entails tailored tissue extraction and growth protocols, propagation requires consistent multiplication and passaging, while drug screening and response prediction will benefit from shorter and more precise assays, and clear decision-making tools. Conclusions This review attempts to outline the most important challenges that remain in exploiting organoid platforms for drug discovery and clinical applications. Some of these challenges may be overcome by novel methods that are under investigation, such as 3D bioprinting systems, microfluidic systems, optical metabolic imaging and liquid handling robotics. We also propose an optimized organoid workflow inspired by all technical solutions we have presented.

scholarly journals Plasma Metabolome Profiling Identifies Metabolic Subtypes of Pancreatic Ductal Adenocarcinoma

Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1821
Author(s):  
Ujjwal Mukund Mahajan ◽  
Ahmed Alnatsha ◽  
Qi Li ◽  
Bettina Oehrle ◽  
Frank-Ulrich Weiss ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Enrichment Analysis ◽  
Response Prediction ◽  
Ductal Adenocarcinoma ◽  
Pathway Enrichment Analysis ◽  
Metabolome Analysis ◽  
Dismal Prognosis ◽  
Chemotherapeutic Response ◽  
Plasma Metabolome ◽  
Metabolome Profiling

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Developing biomarkers for early detection and chemotherapeutic response prediction is crucial to improve the dismal prognosis of PDAC patients. However, molecular cancer signatures based on transcriptome analysis do not reflect intratumoral heterogeneity. To explore a more accurate stratification of PDAC phenotypes in an easily accessible matrix, plasma metabolome analysis using MxP® Global Profiling and MxP® Lipidomics was performed in 361 PDAC patients. We identified three metabolic PDAC subtypes associated with distinct complex lipid patterns. Subtype 1 was associated with reduced ceramide levels and a strong enrichment of triacylglycerols. Subtype 2 demonstrated increased abundance of ceramides, sphingomyelin and other complex sphingolipids, whereas subtype 3 showed decreased levels of sphingolipid metabolites in plasma. Pathway enrichment analysis revealed that sphingolipid-related pathways differ most among subtypes. Weighted correlation network analysis (WGCNA) implied PDAC subtypes differed in their metabolic programs. Interestingly, a reduced expression among related pathway genes in tumor tissue was associated with the lowest survival rate. However, our metabolic PDAC subtypes did not show any correlation to the described molecular PDAC subtypes. Our findings pave the way for further studies investigating sphingolipids metabolisms in PDAC.

scholarly journals Pancreatic Ductal Adenocarcinoma (PDAC) Organoids: The Shining Light at the End of the Tunnel for Drug Response Prediction and Personalized Medicine

Cancers ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2750
Author(s):  
Pierre-Olivier Frappart ◽  
Thomas G. Hofmann
Keyword(s):  
Personalized Medicine ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Drug Response ◽  
Treatment Options ◽  
Response Prediction ◽  
Ductal Adenocarcinoma ◽  
Chemotherapy Treatment ◽  
The Past ◽  
Therapeutic Tools ◽  
And Personalized Medicine

Pancreatic ductal adenocarcinoma (PDAC) represents 90% of pancreatic malignancies. In contrast to many other tumor entities, the prognosis of PDAC has not significantly improved during the past thirty years. Patients are often diagnosed too late, leading to an overall five-year survival rate below 10%. More dramatically, PDAC cases are on the rise and it is expected to become the second leading cause of death by cancer in western countries by 2030. Currently, the use of gemcitabine/nab-paclitaxel or FOLFIRINOX remains the standard chemotherapy treatment but still with limited efficiency. There is an urgent need for the development of early diagnostic and therapeutic tools. To this point, in the past 5 years, organoid technology has emerged as a revolution in the field of PDAC personalized medicine. Here, we are reviewing and discussing the current technical and scientific knowledge on PDAC organoids, their future perspectives, and how they can represent a game change in the fight against PDAC by improving both diagnosis and treatment options.

Grafting of 3D Bioprinting to In Vitro Drug Screening: A Review

2020 ◽  
Vol 9 (7) ◽  
pp. 1901773 ◽  
Author(s):  
Jing Nie ◽  
Qing Gao ◽  
Jianzhong Fu ◽  
Yong He
Keyword(s):  
Drug Screening ◽  
3D Bioprinting ◽  
In Vitro Drug Screening

scholarly journals 3D bioprinting of functional tissue models for personalized drug screening and in vitro disease modeling

2018 ◽  
Vol 132 ◽  
pp. 235-251 ◽  
Author(s):  
Xuanyi Ma ◽  
Justin Liu ◽  
Wei Zhu ◽  
Min Tang ◽  
Natalie Lawrence ◽  
...  
Keyword(s):  
Drug Screening ◽  
Disease Modeling ◽  
3D Bioprinting ◽  
Functional Tissue ◽  
Tissue Models

Sa1154 ORGANOID-BASED PRECLINICAL MODELS RECAPITULATE RENALASE SIGNALING IN PANCREATIC DUCTAL ADENOCARCINOMA

2020 ◽  
Vol 158 (6) ◽  
pp. S-293
Author(s):  
Govind Krishna Kumar Nair ◽  
Jin Woo (Gene) Yoo ◽  
Yasheen Gao ◽  
Gary Desir ◽  
Fred S. Gorelick ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Ductal Adenocarcinoma ◽  
Preclinical Models

scholarly journals 3D bioprinting of glioblastoma models

2020 ◽  
Vol 4 (2) ◽  
pp. 113-125
Author(s):  
Carolina Parra-Cantu ◽  
Wanlu Li ◽  
Alfredo Quiñones-Hinojosa ◽  
Yu Shrike Zhang
Keyword(s):  
Brain Tumor ◽  
Drug Screening ◽  
Antineoplastic Agents ◽  
Primary Brain Tumor ◽  
3D Bioprinting ◽  
Brain Models

The most common and malignant primary brain tumor in adults is glioblastoma (GBM). In vitro 3D brain models are needed to better understand the pathological processes underlying GBM and ultimately develop more efficient antineoplastic agents. Here, we describe the bioprinting methods that have been used to fabricate volumetric GBM models. We explain several factors that should be considered for 3D bioprinting, including bioinks, cells and construct designs, in relation to GBM modeling. Although 3D-bioprinted brain models are still to be improved, they have the potential to become a powerful tool for drug screening.

scholarly journals Evaluation of Liquid Handling Conditions in Microplates

2001 ◽  
Vol 6 (1) ◽  
pp. 47-56 ◽  
Author(s):  
Michael Berg ◽  
Katrin Undisz ◽  
Ralf Thiericke ◽  
Peter Zimmermann ◽  
Thomas Moore ◽  
...  
Keyword(s):  
Drug Screening ◽  
Evaluation Studies ◽  
Bubble Formation ◽  
Liquid Handling ◽  
Mixing Behavior

Liquid handling in higher density microplates (e.g., 1536-well microplates) for more efficient drug screening necessitates carefully selected and optimized parameters. The quality of a liquid handling procedure is dependent on the carryover rate of residual liquids during the pipetting process, the mixing behavior in the wells, foam and bubble formation, and evaporation. We compared and optimized these parameters in 96-, 384-, and 1536-well microplates, and herein we critically evaluate the performance of the CyBi™-Well 96/384/1536 automated micropipetting device, which formed the basis of our evaluation studies.

scholarly journals Preclinical models of pancreatic ductal adenocarcinoma: challenges and opportunities in the era of precision medicine

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
Yiqi Yu ◽  
Gang Yang ◽  
Hua Huang ◽  
Ziyao Fu ◽  
Zhe Cao ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Ductal Adenocarcinoma ◽  
Steady Increase ◽  
Targeted Therapeutics ◽  
Preclinical Models ◽  
High Quality ◽  
Limited Efficacy ◽  
Conventional Regimen ◽  
Challenges And Opportunities

AbstractPancreatic ductal adenocarcinoma (PDAC) is an extremely lethal malignancy, with an average 5-year survival rate of 9% (Siegel RL, Miller KD, Jemal A. Ca Cancer J Clin. 2019;69(1):7-34). The steady increase in mortality rate indicates limited efficacy of the conventional regimen. The heterogeneity of PDAC calls for personalized treatment in clinical practice, which requires the construction of a preclinical system for generating patient-derived models. Currently, the lack of high-quality preclinical models results in ineffective translation of novel targeted therapeutics. This review summarizes applications of commonly used models, discusses major difficulties in PDAC model construction and provides recommendations for integrating workflows for precision medicine.

Optimized preclinical models for human pancreatic adenocarcinoma therapy research

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 15019-15019
Author(s):  
N. Carbó ◽  
S. Pérez-Torras ◽  
A. Vidal-Pla ◽  
R. Miquel ◽  
V. Almendro ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Pancreatic Adenocarcinoma ◽  
Expression Patterns ◽  
Resistance Mechanisms ◽  
Tissue Array ◽  
Ductal Adenocarcinoma ◽  
Preclinical Models ◽  
Biological Behaviour ◽  
Primary Tumors ◽  
Effective Development

15019 Background: Efforts to find new therapies for human pancreatic ductal adenocarcinoma (PDAC) have not resulted in clear improvements on patient survival. Better knowledge of resistance mechanisms and redefiniton of molecular targets is essential to design more efficient therapies. The multifactorial origin of PDAC points to combined strategies as the therapy of choice, though the effective development of such strategies is hampered by the lack of optimal preclinical models. We have generated and validated optimized human PDAC models by direct implantation of fresh tumoral tissue into the pancreas of athymic mice. Methods: Thirteen pancreatic adenocarcinoma specimens from PDAC patients were obtained by surgical resection. From each specimen, several 10 mg-fragments were used to generate the corresponding intrapancreatic xenografted tumours. Eleven human PDAC orthotopic models have been successfully generated and perpetuated by succesive passages (up to 4). Histological and molecular analyses of both primary and xenografted tumors have been performed by tissue- array, western-blot and DNA sequentiation. Results: Initial engraftment rate ranged from 20 to 100% (mean 59%) and it improved with succesive passages (mean 76% at second and 90% at third generation). Ki67 expression and degree of differentiation in primary tumors correlated with xenograft growth kinetics. Furthermore, their spontaneous metastatic behaviour fairly reproduced the original patient dissemination patterns. Xenografted tumors kept the original architecture and expression patterns of common PDAC markers. Efficacy of several agents was tested on different xenografted tumors, validating this model and underlining its utility to define future therapeutic strategies for drug development and clinical trials. Conclusions: The orthotopic models described here are, probably, the closest resemblance to a patient clinical setting since they preserve human pancreatic structures, genotypic features and biological behaviour. From their use, biological relevant data could be drawn for future clinical trials and for testing new agents and new drug combinations since they represent, very likely, the most reliable animal models at present. No significant financial relationships to disclose.

scholarly journals Novel Drug Screening Platform: Tumor Organoid

2021 ◽  
Vol 26 (4) ◽  
pp. 233-240
Author(s):  
Ju Eun Maeng ◽  
Ha-Young Seo ◽  
Soon-Chan Kim ◽  
Ja-Lok Ku
Keyword(s):  
Drug Screening ◽  
Tumor Tissue ◽  
Ductal Adenocarcinoma ◽  
Personalized Cancer Medicine ◽  
Cancer Types ◽  
Screening Platform ◽  
And Function ◽  
Personalized Cancer ◽  
Novel Drug ◽  
Fitting Model

Pancreatic ductal adenocarcinoma (PDAC) is known to be one of the most lethal cancers among all cancer types, with a relative 5-year survival rate of less than 8%. Currently, surgery is the only probable curative treatment for PDAC which is available for only 10-15% of the patients diagnosed with the cancer. Organoids resemble the original tissue in morphology and function with self-organizing capacity. Organoids can be cultured with high effectiveness from individual patient derived tumor tissue which makes them an extremely fitting model for translational uses and the improvement of personalized cancer medicine. Before personalized medicine based on organoids can be applied in the clinic, the improvement of drug screening platforms in terms of sensitivity and robustness is necessary.

Sign in / Sign up

Export Citation Format

Share Document